The Dissertation
Topics Covered
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Structure
Length
Key Issues
How to Present Key Types of Research
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Interviews
Surveys
Experimentation
Statistics
Dissertation Structure
Dissertation Overview
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For all details related to dissertation layout, templates,
deadlines, checklists etc.
http://www.comp.dit.ie/btierney/MScDissertations/index.h
tml
Aim for 100 pages
Dissertation Structure
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Title
Abstract
Table of Contents
Table of Figures
Table of Tables
Introduction (starts at page 1)
Literature Review (can be separate chapters)
Your Design
Your Findings
Your Evaluation
Conclusion and Future Work
Introduction
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Aim is to introduce the reader to
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The project
Its background
Justification that the project is viable
Your project aims
You project objectives
Your research approach
Any scope or limitations
Overview of the rest of the dissertation
10-15 pages (approx. 10% of the dissertation)
Background/Literature Review
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Aim is to provide the reader with your insight into the
body of literature
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Introduce key terms, definitions, ideas, thought leaders
Provide critical analysis of existing approaches, techniques etc.
Identify key ideas, themes, issues or directions that informed
your approach
Set the scene for why you will be doing things the way you will
do things for your project
20-25 pages (approx. 20- 25% of the dissertation)
Can be split into multiple chapters
Your Project = 60% of the dissertation
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Generally you need a chapter for each of the following:
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Design/Formulation of proposed
experimentation/implementation
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Experimentation/Implementation
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Should be clear how the literature reviewed has influenced design
Should be clear why research approach is suitable
Should align with proposed approach
Should discuss clearly any deviation/adjustments needed with
justification
Analysis of your findings
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Should honestly discuss the outcome of your experimentation
Should draw conclusions about your work
Conclusion and Future work
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Approx. 10% of dissertation
Should mirror your introduction
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Should address how well you have addressed the aim and
objectives
Should assess where and how well your work aligns with
existing research
Should discuss scope and limitations
Should provide detail about potential future work
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To build on your experimentation
Alternates to your experimentation
Other avenues in which your work can be applied
Etc.
Interviews
The Interview
Interviewer
Interviewee
Interview
Issues to be Discussed – Interview Design
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Justification for use as a tool
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Relate back to qualitative
research
Relate to your project
State clearly
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Interview Aims
Interview Objectives
Relationship to project
Choice of Interviewees
(audience, sample)
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Profile
Skills
Justification of suitability
Make transparent any
constraints
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Question design
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Each question should address
certain objectives
Outline clearly this
relationship
Think clearly about the
question wording
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Is it suitable for your
interviewees?
Is it suitable to elicit the
knowledge you need?
Issues to be Discussed – Interview
Execution
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Who
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When
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How long, one to one, recorded, over Skype etc.
What
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Location, surroundings, anything that influenced
How
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Dates, times, duration
Where
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Profile, how many etc.
Exactly what happened, any issues – hesitancy, lack of understanding
of questions, additional questions, suggestions etc.
Why
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For all the above why were things done in this way, why did certain
things happen etc.
Issues to be Discussed – Interview Findings
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Transcribe your interviews
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You need to include the
transcription
Not within the main dissertation
but as an appendix
Can be included on a CD
Analyse your data
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Summarise, organise and extract
meaning from interview transcripts
Coding
Identify Major Themes
Align to aims and objectives
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Of interview
Of project
To literature
Present summary statistics
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Draw Conclusions
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Be aware of bias
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Determine key issues to be
addressed
Identify recommendations
Make it transparent
Validate findings and conclusions
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Expose to some interviewees
Look for independent verification –
literature, other research tools
used
Review and revise conclusions to
ensure that they are reliable and
valid
Bias
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What is bias?
 All views of reality are filtered.
 Bias only exists in relation to some reference point.
Types of bias:
 Motivational bias
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Observational bias
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Limitations on our ability to accurately observe the world
Cognitive bias
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Interviewee makes accommodations to please the interviewer or some other
audience
Mistakes in use of statistics, estimation, memory, etc.
Notational bias
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Terms used to describe a problem may affect our understanding of it
Examples
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Social pressure
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response to imagined reactions of
managers, clients,…
Wishful thinking
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response to reactions of other
experts
Impression management
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response to verbal and non-verbal
cues from interviewer
Group think
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response to hopes or possible gains
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selective interpretation to support
current beliefs
assumptions made earlier are
forgotten
Availability
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contradictory data ignored once
initial solution is available
Inconsistency
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expert cannot accurately fit a
response into the requested
response mode
Anchoring
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Appropriation
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Misrepresentation
some data are easier to recall than
others
Underestimation of uncertainty
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tendency to underestimate by a
factor of 2 or 3
Terminology
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Theme
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a topic that organizes a group
of repeating ideas.
usually developed during
focused coding, but may emerge
during literature supported by
interview findings
E.g. from analysis of interviewee
responses, it emerged that that
employees are reluctant to use
the Wiki as they view the
contents as out of date and
stagnant.
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Making
conclusions/recommendation
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a determination of what is
working well and what needs to
be improved based on repeating
ideas and themes.
Themes and repeating ideas
should guide you in
recommending or making
improvements.
E.g. in response to the view of
the Wiki as stagnant and out of
date, the project will introduce
social media tools alongside the
Wiki to encourage more
informal knowledge sharing
Issues to be Discussed – Interview Findings
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Report repeating
ideas/issues
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Those that most exemplify
issues or support
recommendations
Quantify these
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Present Graphically
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Repeated by a number of
interviewees
Report meaningful
responses
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How many people said this?
How many disagreed?
Why are they best situated to
comment?
Include quotes
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Organise themes and
conclusions into tables or
trees
Demonstrate relationships
Interviews
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Unstructured interview
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Semi-structured interview
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Free flowing, used in early stages of elicitation/research, can
produce basics of knowledge domain, basically broad chat
Main technique
Pre-defined questions sent to expert prior to interview,
supplementary questions asked at interview. Can be used as
part of validation.
Structured interview
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Pre-defined set of questions, can simply be filling in a
questionnaire at the interview.
Kvale’s Seven Stages
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Themazing
Designing
Interviewing
Transcribing
Analyzing
Verifying
Reporting
Interview Questions
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Introductory Questions
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Exact information
Transitioning to new topics
Interpreting Question
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Projective questions
Structuring Questions
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Introducing a new topic
Indirect Questions
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Unlimited scope question
Specifying Questions
Direct Questions
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Listen for “Red Lights”
Probing Questions
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Warm up questions
Followup Questions
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Clarifying questions
Silences
A.N. Oppenheim, Questionnaire Design
Questionnaires/Surveys
Issues to be Discussed –Design
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Justification for use as a tool
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Relate back to qualitative research
Relate to your project
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State clearly
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Aims
Objectives
Relationship to project
Choice of audience
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Each question should address
certain objectives
Outline clearly this relationship
Think clearly about the question
wording
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Profile
Skills
Justification of suitability
Size of sample
Explain distribution mechanism
Make transparent any constraints
Question design
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Think clearly about the question
design
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Is it suitable for your interviewees?
Is it suitable to elicit the knowledge
you need?
Multi-choice, open text etc.
Justify
How long will it table to
complete?
Check your grammar, twice (Rule
of Thumb – two proofreads gets
rid of 95% of errors).
Issues to be Discussed
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Who
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When
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Email, paper etc.
What
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Geographic location
How
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Dates, times, duration
Where
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Profile, how many targeted, how many responses etc.
Exactly what happened, any issues –omissions, lack of understanding
of questions, additional questions, suggestions etc.
Why
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For all the above why were things done in this way, why did certain
things happen etc.
Issues to be Discussed – Survey Findings
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Collate your findings
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You need to include the collated
responses
Not within the main dissertation
but as an appendix
Can be included on a CD
Report summarised responses
Analyse your data
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Summarise, organise and extract
meaning from responses
Coding
Identify Major Themes
Align to aims and objectives
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Of interview
Of project
To literature
Present summary statistics for
survey overall
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Draw Conclusions
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Be aware of bias
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Determine key issues to be
addressed
Identify recommendations
Make it transparent
Validate findings and conclusions
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Look for independent verification –
literature, other research tools
used
Review and revise conclusions to
ensure that they are reliable and
valid
Issues to be Discussed – Survey Findings
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Present summary statistics for
question responses (for key
questions)
Report repeating ideas/issues
Report meaningful responses
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Quantify these
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Those that most exemplify
issues or support
recommendations
How many people said this?
How many disagreed?
Why are they best situated to
comment?
Include quotes
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Present Graphically
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Present outcomes of key
questions or question groupings
as charts or diagrams
Organise themes and
conclusions into tables or trees
Demonstrate relationships
Questionnaires
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Keep questions short and simple
Avoid questions with “not”
Avoid questions with bias
Avoid sensitive questions (ask indirectly)
Do not ask compound questions, just ask one
question at a time
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e.g. "Do you know what services are available to you and
how to find out?"
Questionnaires
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Likert scales
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Poor, Weak, O.K., Good, Excellent
Very Low, Low, O.K., High, Very High
1, 2, 3, 4, 5
Descriptive and Inferential Statistics
Measure of Central Tendency
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Central position of a frequency distribution for a group of
data
Possible measures: mode, median, and mean.
Mean: The arithmetic average of a group of scores; the
sum of the scores divided by the number of scores.
Median The middle score of a sequence of all the scores
in a distribution arranged from lowest to highest.
Mode The value with the greatest frequency on the
distribution
Examples
Measures of spread
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Ways of summarizing a group of data by describing how
spread out the results/findings
Normal Curve: A specific, mathematically defined, bell-shaped
frequency distribution that is symmetrical and unimodal;
Normal Distribution: A frequency distribution following a
normal curve.
Skewness: The extent to which the majority of cases in a
frequency distribution fall to one side of the middle.
Inter-quartile range: The range of the middle 50 per cent of all
scores in a distribution when arranged from lowest to highest.
Standard Deviation: A measure of the degree to which scores
in a distribution vary from the mean.
Variance Another measure of the degree to which scores in a
distribution vary from the mean (equal to the standard
deviation squared).
Way to Present Data
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Interval or Ratio Variables
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Mean and Standard Deviation (if approximately normally
distributed)
Median and Interquartile Range (if skewed and thus not
normally distributed)
Histograms
Boxplots
Stem-and-Leaf Displays
Interval variable: A variable with actual values rather than
categories e.g. salary
Ration variable: As with interval variable but with added
characteristic that there is a true zero value e.g. age
Way to Present Data
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Ordinal or Nominal
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Mode and/or simple frequencies
Barcharts
Piecharts
Tables
Nominal variable: A variable that consists of two
or more categories. E.g. male or female
Ordinal variable: A variable that consists of categories that
can be rank ordered in relation to being 'more' or 'less' of
the concept in question. E.g. age ranges 16-20 etc.